Non-invasive Transcutaneous Spinal Cord Stimulation Programming Recommendations for the Treatment of Upper Extremity Impairment in Tetraplegia
Bibliographic record
Abstract
OBJECTIVES: This study analyzes the stimulation parameters implemented during two successful trials that used non-invasive transcutaneous spinal cord stimulation (tSCS) to effectively improve upper extremity function after chronic spinal cord injury (SCI). It proposes a framework to guide stimulation programming decisions for the successful translation of these techniques into the clinic. MATERIALS AND METHODS: Programming data from 60 participants who completed the Up-LIFT trial and from 17 participants who subsequently completed the LIFT Home trial were analyzed. All observations of stimulation amplitudes, frequencies, waveforms, and electrode configurations were examined. The incidence of adverse events and relatedness to stimulation parameters is reported. A comparison of parameter usage across the American Spinal Injury Association Impairment Scale (AIS) subgroups was conducted to evaluate stimulation strategies across participants with varying degrees of sensorimotor preservation. RESULTS: Active (cathodal) electrodes were typically placed between the C3/C4 and C6/C7 spinous processes. Most sessions featured return (anodal) electrodes positioned bilaterally over the anterior superior iliac spine, although clavicular placement was frequently used by 12 participants. Stimulation was delivered with a 10-kHz carrier frequency and typically a 30-Hz burst frequency. Biphasic waveforms were used in 83% of sessions. Average stimulation amplitudes were higher for biphasic waveforms. The AIS B subgroup required significantly higher amplitudes than did the AIS C and D subgroups. Device-related adverse events were infrequent, and not correlated with specific waveforms or amplitudes. Within the home setting, participants maintained their current amplitudes within 1% of the preset values. The suggested stimulation programming framework dictates the following hierarchical order of parameter adjustments: current amplitude, waveform type, active/return electrode positioning, and burst frequency, guided by clinical observations as required. CONCLUSIONS: This analysis summarizes effective stimulation parameters from the trials and provides a decision-making framework for clinical implementation of tSCS for upper extremity functional restoration after SCI. The parameters are aligned with existing literature and proved safe and well tolerated by participants.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".